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Due to what has been termed "the failure of the polls" in a series of elections (e.g., UK, 1992; Germany, 2005), every country with election polling has heard calls for greater regulation of the polls, including calls for an outright ban. At least 30 different nations currently place some sort of embargo on the publication of results from election polls. The debate is fuelled by the concern that if political information is a key component of democratic elections then a functioning democracy requires unbiased information. Even free from bias, though, political information derived from polls may be troublesome. This is due to the multiplicity of mechanisms through which polls can have their effect on voters. Unfortunately, not enough is known about the effect of poll information on voters or about the polls themselves to properly conduct this debate. The key methodological challenge is in finding campaign poll effects on individual vote intentions. The challenges of finding any campaign effects on public opinion are vast, not the least of which is the endogeniety of campaign media coverage in a model of public opinion. This is many times worse for campaign polls, as the effect of the event (published vote intentions from a poll) is measured by a subsequent poll which is likely to be influenced by forces which are highly correlated with the previous poll. In this paper, I will demonstrate how to use a multilevel logistic regression with an autoregressive error process at the campaign day level, estimated using MCMC methods, to determine the effects of published polls on vote intention at the individual level, while controlling for endogeniety.
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CSES-Bibliography
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?:name
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Sifting through the endogeneity: How to measure the effect of a campaign poll with a poll
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inproceedings
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4th General Conference of the European Consortium for Political Research
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Bibsonomy
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In 4th General Conference of the European Consortium for Political Research, 2007
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Comparative Study of Electoral Systems (CSES)
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2007
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CSES
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inproceedings
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